Evaluation of ELISA tests for the qualitative determination of IgG, IgM and IgA to SARS-CoV-2

  1. Colavita Francesca
  2. Brogi Alessandra
  3. Lapa Daniele
  4. Bordi Licia
  5. Matusali Giulia
  6. Meschi Silvia
  7. Marsella Patrizia
  8. Tesi Giulia
  9. Bandini Tommaso
  10. Di Caro Antonino
  11. Capobianchi Maria Rosaria
  12. Castilletti Concetta

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Abstract

Serological assays for anti-SARS-CoV-2 antibodies are now of critical importance to support diagnosis, guide epidemiological intervention, and understand immune response to natural infection and vaccine administration. We developed and validated new anti-SARS-CoV-2 IgG, IgM and IgA ELISA tests (ENZY-WELL SARS-CoV-2 ELISA, DIESSE Diagnostica Senese S.p.a.) based on whole-virus antigens. We used a total of 553 serum samples including samples from COVID-19 suspected and confirmed cases, healthy donors, and patients positive for other infections or autoimmune conditions. Overall, the assays showed good concordance with the indirect immunofluorescence reference test in terms of sensitivity and specificity. Especially for IgG and IgA, we observed high sensitivity (92.5 and 93.6%, respectively); specificity was high (>96%) for all antibody types ELISAs. In addition, sensitivity was linked to the days from symptoms onset (DSO) due to the seroconversion window, and for ENZY-WELL SARS-CoV-2 IgG and IgA ELISAs resulted 100% in those samples collected after 10 and 12 DSO, respectively. The results showed that ENZY-WELL SARS-CoV-2 ELISAs may represent a valid option for both diagnostic and epidemiological purposes, covering all different antibody types developed in SARS-CoV-2 immune response.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.24.20111682: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved from the INMI Ethical Board.
    Consent: Informed consent was not required as human samples used for this work were residual samples from routine diagnostic activities, patients’ data remained anonymous, and the results obtained with the new tests were not used for the clinical management of the patient.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line AuthenticationContamination: A group of 21 samples from patients who had been diagnosed with seasonal human coronaviruses (HKU, NL63, 229E), and 64 found positive for other infections (i.e. Mycoplasma, Cytomegalovirus, Adenovirus, Respiratory Syncitial

    Table 2: Resources

    Antibodies
    SentencesResources
    virus, Influenza A, Influenza B, SARS-CoV) or interfering factors (i.e. as anti-nuclear antibodies and rheumatoid factor) was included in the analysis, to estimate cross-reactivity.
    anti-nuclear
    suggested: None
    Then, microwells were washed and and anti-human IgG, IgM and IgA monoclonal antibodies, labeled with peroxidase, in phosphate buffer containing phenol 0.05% and Bronidox 0.02%, were added to the microwells (100 μL/well) and incubated at room temperature for 1 hour.
    anti-human IgG
    suggested: None
    IgA
    suggested: None
    Internal quality controls were included in each run: one positive control containing anti-SARS-CoV-2 antibodies; one negative control not containing anti-SARS-CoV-2 antibodies; a cut-off (CO) control with a known concentration of anti-SARS-CoV-2 antibodies.
    anti-SARS-CoV-2
    suggested: None
    FITC-conjugated anti-human IgM, IgA and IgG antibodies (Euroimmun, Germany) were used as secondary antibody and Evans Blue as cell counterstain.
    FITC-conjugated anti-human IgM, IgA
    suggested: None
    IgG antibodies (Euroimmun, Germany)
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    IFA, used as reference test, was performed using slides prepared in-house with Vero E6 cells infected with SARS-CoV-2 isolate (2019-nCoV/Italy-INMI1), as described elsewhere (5).
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    The statistical analysis was performed using GraphPad Prism version 7.00 (GraphPad Software, La Jolla California).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.05.24.20111682 on medRxiv